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  • 标题:Comparison of Frequent Item Set Mining Algorithms
  • 本地全文:下载
  • 作者:J.R.Jeba ; S.P.Victor
  • 期刊名称:International Journal of Computer Science and Information Technologies
  • 电子版ISSN:0975-9646
  • 出版年度:2011
  • 卷号:2
  • 期号:6
  • 页码:2838-2841
  • 出版社:TechScience Publications
  • 摘要:Frequent item sets mining plays an important role in association rules mining. Over the years, a variety of algorithms for finding frequent item sets in very large transaction databases have been developed. The main focus of this paper is to analyze the implementations of the Frequent item set Mining algorithms such as SMine and Apriori Algorithms.
  • 关键词:SMine; item_count; frequent_items.
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